SOTAVerified

Motion Segmentation

Motion Segmentation is an essential task in many applications in Computer Vision and Robotics, such as surveillance, action recognition and scene understanding. The classic way to state the problem is the following: given a set of feature points that are tracked through a sequence of images, the goal is to cluster those trajectories according to the different motions they belong to. It is assumed that the scene contains multiple objects that are moving rigidly and independently in 3D-space.

Source: Robust Motion Segmentation from Pairwise Matches

Papers

Showing 161170 of 212 papers

TitleStatusHype
Vision-based Traffic Flow Prediction using Dynamic Texture Model and Gaussian Process0
Discovering the Physical Parts of an Articulated Object Class From Multiple Videos0
Motion From Structure (MfS): Searching for 3D Objects in Cluttered Point Trajectories0
ReD-SFA: Relation Discovery Based Slow Feature Analysis for Trajectory Clustering0
A Continuous Occlusion Model for Road Scene Understanding0
Dense Monocular Depth Estimation in Complex Dynamic Scenes0
Achieving stable subspace clustering by post-processing generic clustering results0
Quickest Moving Object Detection0
Parametric Object Motion from Blur0
It's Moving! A Probabilistic Model for Causal Motion Segmentation in Moving Camera Videos0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Rule BasedAccuracy90Unverified
2Rel-Att-GCNAccuracy89Unverified
3MRGCNAccuracy86Unverified
4MRGCN-LSTMAccuracy72Unverified
5St-RNNAccuracy63Unverified
#ModelMetricClaimedVerifiedStatus
1SSCClassification Error2.18Unverified
2T-LinkageClassification Error1.97Unverified
3RSIMClassification Error1.01Unverified
4MVCClassification Error0.31Unverified
#ModelMetricClaimedVerifiedStatus
1MultiViewClusteringError7.92Unverified
#ModelMetricClaimedVerifiedStatus
1MVCClassification Error0.65Unverified